WO2023225811A1

WO2023225811A1 - Method and apparatus for assisting with driving, and vehicle

Info

Publication number: WO2023225811A1
Application number: PCT/CN2022/094524
Authority: WO
Inventors: 陈柏佚; 胡文潇
Original assignee: 华为技术有限公司
Priority date: 2022-05-23
Filing date: 2022-05-23
Publication date: 2023-11-30
Also published as: CN117651669A

Abstract

Provided in the embodiments of the present application are a method and apparatus for assisting with driving, and a vehicle. The method comprises: acquiring real-time travelling parameters while a driver drives a vehicle and surroundings information of the vehicle; determining a driving habit of the driver according to the real-time travelling parameters and the surroundings information; and when the driving habit meets a first preset condition, prompting the driver with driving reminder information. The method for assisting with driving in the embodiments of the present application can be applied to new energy vehicles or intelligent vehicles. A driving habit of a driver can be determined in real time in the process of the driver driving a vehicle, and thereby a targeted driving reminder can be given according to the driving habit of the driver. A driver having poor driving habits can be helped to learn and/or consolidate matters for attention during driving, thereby helping the driver to develop good driving habits and facilitating the improvement in the driving safety.

Description

Methods, devices and vehicles for assisted driving

Technical field

The present application relates to the field of intelligent driving, and more specifically, to a method, device and vehicle for assisted driving.

Background technique

With the upgrade of chip and algorithm performance, intelligent driving functions are developing towards fully autonomous driving. However, due to the multiple restrictions on the implementation of fully autonomous driving, human-machine co-driving will become the norm in the development of intelligent driving. Vehicles with human-machine collaborative driving can better cope with road risks and obtain a better driving experience. In the human driving mode, most traffic violations are caused by incorrect driving habits. In the process of a driver changing from a novice to a skilled driver, it is difficult to form good driving habits and maintain them.

In view of this, a method, device and vehicle for assisted driving urgently need to be developed.

Contents of the invention

This application provides a driving assistance method, device and vehicle that can identify drivers with different driving habits and provide adaptive reminders based on the driver's driving habits, thereby improving the driver's driving experience and driving safety.

The vehicle (sometimes referred to as a vehicle) in this application is a vehicle in a broad sense, which can be a means of transportation (such as a car, a truck, a motorcycle, a train, an airplane, a ship, etc.), an industrial vehicle (such as a forklift, a trailer, a tractor, etc.) vehicles, etc.), engineering vehicles (such as excavators, bulldozers, cranes, etc.), agricultural equipment (such as lawn mowers, harvesters, etc.), amusement equipment, toy vehicles, etc. This application does not limit the types of vehicles.

The first aspect provides a method of assisting driving, which can be executed by a vehicle; or it can also be executed by a vehicle-mounted terminal such as a vehicle machine; or it can also be executed by a chip or circuit for the vehicle. This method There are no restrictions on this application. For ease of description, device execution is taken as an example for description below. It should be understood that the device can be provided in a vehicle-mounted terminal or in other hardware equipment, which is not specifically limited in this application.

The method may include: obtaining the real-time driving parameters of the driver when driving the vehicle and the surrounding environment information of the vehicle; determining the driver's driving habits based on the real-time driving parameters and the surrounding environment information; and when the driving habits satisfy the first preset When conditions are met, driving reminder information is prompted to the driver.

In the above technical solution, the driver's driving habits can be determined based on the vehicle driving parameters and the vehicle's surrounding environment data obtained in real time when the driver drives the vehicle. It should be understood that the driving habits refer to the driver's driving activities during long periods of time. Driving behavior or driving tendency that is gradually developed and cannot be easily changed for a while. Furthermore, it can be determined based on the driver's driving habits whether to provide driving reminders while the vehicle is driving, which helps drivers with poor driving habits improve their driving behavior. Especially in the field of shared cars, the driver may be different every time he or she uses the vehicle, and the driving habits of the drivers may also vary. In this case, real-time acquisition of driving data and determination of the driver's driving habits can help drivers with poor driving habits learn and/or consolidate what they need to pay attention to during driving by prompting driving reminder information to drivers with poor driving habits. It helps drivers develop good driving habits and improves driving safety.

It should be noted that the real-time driving data may include driving data obtained from the time the driver starts the vehicle during the current trip of the vehicle, or may also include driving data obtained from the first time, which is the current time. The time is moved forward by a preset duration. For example, the preset duration may be 20 minutes, or it may be 40 minutes, or it may be other durations.

For example, real-time driving parameters include but are not limited to: vehicle speed, vehicle acceleration, accelerator opening during acceleration, vehicle deceleration, brake opening during deceleration, steering wheel angle and turning rate during turning, and parking time. . Surrounding environment information includes but is not limited to: road information (such as congestion, pedestrians around, curves, traffic signs, etc.), surrounding vehicle information (such as the distance to the vehicle in front).

In some possible implementations, it can be determined based on the vehicle's real-time driving parameters and the vehicle's surrounding environment information whether there is speeding, failure to yield, being too close to the vehicle in front, illegal temporary parking, and violation of traffic regulations during driving, and then based on The weight of speeding, failure to yield, being too close to the vehicle in front, illegal temporary parking, and violation of traffic regulations determines the driver's driving habits.

In some possible implementations, the driver's driving habits can be characterized according to the driving habit scores. An example: Score _{(Driving Habits)} =a ₁₊ a ₂₊ a ₃₊ a ₄₊ a ₅ . Among them, a ₁ to a ₅ respectively represent the weight of vehicle speed, yield, vehicle distance, temporary parking, and traffic regulations. The value of a ₁ to a ₅ can be any real number between 0 and 1. The higher the Score _(Driving _Habits) The smaller the value, the worse the driving habits. In the above case, "driving habits satisfy the first preset condition" may include: Score _{(Driving Habits)} is less than a first preset threshold, which represents a good driving habit score, such as 3 or 4. As another example, the driving habit score Score _{(Driving Habits)} =a ₁₊ a ₂₊ a ₃₊ a ₄₊ a ₅₊ a ₆ . Among them, a ₆ represents the weight of other driving behaviors, such _as forward collision warning (FCW) and forced ADAS disengagement. The value of a ₆ can be from 0 to 1 any real number in between. In the above case, "driving habits satisfy the first preset condition" may include: Score _{(Driving Habits)} is less than a second preset threshold, which represents a good driving habit score, such as 4 or 5.

With reference to the first aspect, in some implementations of the first aspect, the method further includes: determining the driver's driving experience according to the real-time driving parameters; wherein, when the driving habit satisfies the first preset condition, the method further includes: Prompting driving reminder information to the driver includes: prompting the driver with the driving reminder information when the driving habit satisfies the first preset condition and the driving experience satisfies the second preset condition.

It should be understood that driving experience is used to characterize the driver's proficiency in driving a vehicle and/or the length of driving experience.

In some possible implementations, the driver's driving experience is determined based on at least one of acceleration data, deceleration data, and steering data when the driver drives the vehicle. For example, "driving experience satisfies the second preset condition" may include at least one of the following: the deceleration data of the driver while driving the vehicle falls within the range representing insufficient driving experience in the deceleration Gaussian model; The acceleration data falls within the range that represents insufficient driving experience in the acceleration Gaussian model, and the steering data during the driver's driving process falls within the range that represents insufficient driving experience in the steering Gaussian model.

In some possible implementations, the driver's driving experience can also be determined based on real-time driving parameters and surrounding environment data. As an example, the driver's driving experience is determined based on the parking space type in the surrounding environment data and the driver's parking time while driving the vehicle. "The driving experience satisfies the second preset condition" may include the parking time in this type of parking space. The last x% of the required duration interval, x can be 50, 60, or other values. As another example, the braking smoothness of the vehicle on a certain road section can be determined based on the brake opening and braking action duration in the real-time driving parameters. Furthermore, the driver's driving experience can be determined based on the road information and braking smoothness in the surrounding environment data. , "driving experience meets the second preset condition" may include that if the deceleration smoothness of the own vehicle during this driving trip is at the bottom y% of the deceleration smoothness value interval on the current road segment, x may take the value of 50, or 60, or It can also be other values.

In the above technical solution, by prompting driving reminder information to drivers with poor driving habits and insufficient driving experience, it helps the driver learn and/or consolidate driving experience, assists the driver to develop good driving habits, and improves driving. Experience can also help improve driving safety.

In connection with the first aspect, in some implementations of the first aspect, the method further includes: when detecting that the vehicle speed exceeds the preset speed, prompting the driver with vehicle speed reminder information, and the vehicle speed reminder information is used to remind to slow down. and/or the recommended vehicle speed; and/or when the other road user is detected, prompt the driver with yield indication information, which is used to remind the driver to give way to the other road user; and/or when the other road user is detected, the yield indication information is prompted to the driver. When the distance between the vehicle and the vehicle in front is less than or equal to the preset distance, the driver is prompted with the distance reminder information. The distance reminder information is used to remind the driver to maintain the distance between vehicles and/or the recommended distance between vehicles; and/or during detection When the vehicle enters the restricted parking area, temporary parking reminder information is prompted to the driver. The temporary parking reminder information is used to remind the restricted parking area and/or parking duration; and/or when the vehicle is detected to change lanes, slow down, or When there is at least one of other vehicles behind the vehicle and obstacles on the driving road, a driving observation reminder message is prompted to the driver. The driving observation reminder information is used to prompt the driver to observe illegal and violation reminder information around the vehicle.

In some possible implementations, in different road scenarios, the speed allowed by the road or the speed required for safe driving is different, then it is possible to determine whether the vehicle is overspeeding according to the road scenario, and when it is determined that the vehicle is overspeeding, a speed reminder is prompted to the driver. information. For example, in low-visibility weather such as rain, snow, fog, etc., if it is detected that the vehicle exceeds the preset speed, the driver will be prompted to slow down and/or the recommended speed on the road; or if there are pedestrians and/or around the road When driving to a curve, if it is detected that the vehicle exceeds the preset speed, the driver will be prompted to slow down and/or the recommended speed on the road will be prompted; or, when the vehicle is detected to change lanes and merge into the main road, the vehicle will be detected to be exceeding the preset speed. If the preset speed is set, the driver will be prompted to slow down and/or the driver will be prompted for the recommended speed on the road.

In some possible implementations, the driver can also be prompted with information such as the throttle amplitude and frequency, as well as the braking amplitude and frequency recommended by the driver.

In some possible implementations, the above-mentioned other road users may include vulnerable road users (VRU), such as pedestrians, bicycles, electric vehicles, etc.; or may also include special vehicles, such as police cars, fire trucks, ambulances, etc. vehicles, engineering rescue vehicles, school buses, etc.; or, it may also include other road users other than the own vehicle in certain scenarios. In some possible implementations, when other road users are detected in certain scenarios, a yield prompt message is prompted. For example, at an intersection with no traffic lights, no traffic signs, and no markings, when a vehicle is detected traveling from the right to the left of the own vehicle on the road perpendicular to the own vehicle, the driver is reminded to be aware of other road users. Give way.

For example, the driver can be prompted with the above information through one or more of a vehicle screen, a human machine interface (HMI), a head-up display, an audio-visual system, and other devices.

In some possible implementations, obstacles on the driving road include objects that affect the driver's judgment of the road conditions, including but not limited to: one or more vehicles parked on both sides of the road, other vehicles on the congested road, and other objects that affect the driver's vision. object.

In the above technical solution, the driver is reminded of different driving reminder information based on different driving scenarios, which helps the driver accumulate driving experience and/or improve driving habits for different scenarios. In addition, it also helps improve driving safety.

In conjunction with the first aspect, in some implementations of the first aspect, the method further includes: at the end of the current trip, prompting the data of irregular driving that occurred in the current trip, and/or prompting the data of irregular driving that occurred in the current trip. Comparative results of irregular driving data and irregular driving data that occurred in historical trips.

For example, the data on irregular driving includes behaviors and/or times of irregular driving.

For example, the driver can be prompted with the above information through one or more devices such as a vehicle screen, vehicle audio and video equipment, and a head-up display.

In some possible implementations, if there is no irregular driving behavior during the trip, only the trip route can be displayed, and/or the number of times the driver has completed the standard driving trip can be displayed to encourage the driver to continue to maintain good driving habits.

In the above technical solution, at the end of the driving trip, a summary of driving behavior is helpful to help the driver understand his or her driving performance, deepen the impression, promote the driver to develop good driving habits, and maintain vigilance for safe driving.

Combined with the first aspect, in some implementations of the first aspect, the irregular driving includes the distance between the vehicle and the vehicle in front being less than or equal to the preset distance, failure to give way to other road users, illegal parking, and speeding. Driving or violating at least one of traffic rules.

In connection with the first aspect, in some implementations of the first aspect, when the vehicle travels to the first road section and the first road section supports intelligent driving, the method further includes: prompting the driver to switch the vehicle to intelligent driving. driving mode.

For example, the intelligent driving mode of the vehicle can be a mode in which the vehicle completes driving behaviors such as lane keeping, overtaking and merging, stopping at red lights and running at green lights, and interacting with lights and flutes under the control of an intelligent system (rather than manual); or, The intelligent driving mode can also be a mode in which the vehicle's driving behavior is mainly controlled by the intelligent system. It should be understood that in the latter case, manual intervention in driving behavior is allowed, that is, the driver can respond accordingly to the actual road situation under a series of prompts from the intelligent system.

In some possible implementations, the driver is promptly prompted to take over the vehicle when he is about to travel to a road section that does not support intelligent driving.

In the above technical solution, the driver is supported to switch the vehicle from manual control mode to intelligent driving mode, which helps to reduce the driver's driving burden.

In conjunction with the first aspect, in some implementations of the first aspect, before prompting the driver with the driving reminder information, the method further includes: determining the driving reminder information based on the surrounding environment information.

In conjunction with the first aspect, in some implementations of the first aspect, the real-time driving parameters include a yielding parameter, and the yielding parameter is used to characterize the vehicle's behavior of yielding to other road users during the current trip.

In the above technical solution, the introduction of yield parameters during driving is used to evaluate the driver's driving habits, which helps to reduce the threat to traffic safety caused by drivers who lack the habit of yielding.

In a second aspect, a device for assisting driving is provided. The device includes: an acquisition unit for acquiring real-time driving parameters when the driver drives the vehicle and the surrounding environment information of the vehicle; and a processing unit for obtaining the real-time driving parameters according to the real-time driving parameters. and the surrounding environment information to determine the driver's driving habits; a prompt unit is used to prompt the driver with driving reminder information when the driving habits meet the first preset condition.

In conjunction with the second aspect, in some implementations of the second aspect, the processing unit is further configured to: determine the driver's driving experience based on the real-time driving parameters; the prompting unit is specifically configured to determine when the driving habit satisfies the first preset conditions, and when the driving experience satisfies the second preset condition, the driving reminder information is prompted to the driver.

Combined with the second aspect, in some implementations of the second aspect, the prompt unit is also used to: when detecting that the vehicle speed exceeds the preset speed, prompt the driver with vehicle speed reminder information, and the vehicle speed reminder information is used to Reminders to slow down and/or recommended vehicle speeds; and/or prompt the driver with yield indication information when the other road user is detected, and the yield indication information is used to remind the driver to yield to other road users; and/or When the distance between the vehicle and the vehicle in front is less than or equal to the preset distance, the driver is prompted with a distance reminder message. The distance reminder message is used to remind the driver to maintain the distance between vehicles and/or the recommended distance between vehicles; and/or When it is detected that the vehicle enters the restricted parking area, a temporary parking reminder message is prompted to the driver. The temporary parking reminder message is used to remind the restricted parking area and/or parking duration; and/or when the vehicle is detected to change lanes or slow down. , when there are at least one of other vehicles behind the vehicle and obstacles on the driving road, the driving observation reminder information is prompted to the driver. The driving observation reminder information is used to prompt the driver to observe illegal and violation reminder information around the vehicle.

Combined with the second aspect, in some implementations of the second aspect, the prompt unit is also used to: at the end of the current trip, prompt the data of irregular driving that occurred in the current trip, and/or prompt the data in the current trip. Comparative results of the data on irregular driving that occurred and the data on irregular driving that occurred in historical trips.

Combined with the second aspect, in some implementations of the second aspect, the irregular driving includes the distance between the vehicle and the vehicle in front being less than or equal to the preset distance, failure to give way to other road users, illegal parking, and speeding. Driving or violating at least one of traffic rules.

Combined with the second aspect, in some implementations of the second aspect, when the vehicle travels to the first road section and the first road section supports intelligent driving, the prompt unit is also used to prompt the driver to switch the vehicle to smart driving mode.

In conjunction with the second aspect, in some implementations of the second aspect, the processing unit is further configured to: determine the driving reminder information based on the surrounding environment information before prompting the driver with the driving reminder information.

Combined with the second aspect, in some implementations of the second aspect, the real-time driving parameters include a yielding parameter, and the yielding parameter is used to characterize the vehicle's behavior of yielding to other road users during the current trip.

In a third aspect, a device for assisting driving is provided. The device includes: a memory for storing a program; a processor for executing the program stored in the memory. When the program stored in the memory is executed, the processor is configured to execute the above-mentioned third program. Methods in any of the possible implementations on the one hand.

The fourth aspect provides a driving assistant, which includes one of a virtual image and a physical image. The driving assistant includes at least one processor for executing the method in any possible implementation manner of the first aspect. ; The driving assistant can be carried on at least one of a vehicle screen, a head-up display HUD, a vehicle voice device, and a cockpit.

It should be noted that the driving assistant in the embodiment of the present application may include a virtual image or a physical product. Among them, the virtual image may include a virtual digital person or other virtual image carried on the vehicle screen or head-up display HUD, or a virtual voice assistant carried on the vehicle voice device; the physical product may include a vehicle-mounted small robot carried in the cockpit, etc.

In a fifth aspect, a system for assisting driving is provided. The system includes the device in any of the possible implementations of the second aspect or the third aspect, or the driving assistant in any of the implementations of the fourth aspect.

The sixth aspect provides an intelligent vehicle, which includes the device in any possible implementation of the second aspect or the third aspect, or the driving assistant in any implementation of the fourth aspect, or The system in any implementation manner of the fifth aspect.

In a seventh aspect, a computer program product is provided. The computer program product includes: computer program code. When the computer program code is run on a computer, it causes the computer to execute the method in any of the possible implementation modes of the first aspect. .

It should be noted that the above computer program code may be stored in whole or in part on the first storage medium, where the first storage medium may be packaged together with the processor, or may be packaged separately from the processor. This is not the case in the embodiments of this application. Specific limitations.

In an eighth aspect, a computer-readable medium is provided. The computer-readable medium stores program code. When the computer program code is run on a computer, it causes the computer to execute any of the possible implementation methods of the first aspect. method.

A ninth aspect provides a chip, which includes a processor for calling a computer program or computer instructions stored in a memory, so that the processor executes the method in any of the possible implementations of the first aspect.

Combined with the ninth aspect, in a possible implementation manner, the processor is coupled with the memory through an interface.

In conjunction with the ninth aspect, in a possible implementation manner, the chip system further includes a memory, and a computer program or computer instructions are stored in the memory.

Description of the drawings

Figure 1 is a schematic functional block diagram of a vehicle provided by an embodiment of the present application.

FIG. 2 is a schematic diagram of the system architecture required for the implementation of an assisted driving method provided by an embodiment of the present application.

FIG. 3 is a schematic flow chart of a driving assistance method provided by an embodiment of the present application.

Figure 4 is a schematic diagram of the deceleration Gaussian model provided by the embodiment of the present application.

FIG. 5 is a schematic diagram of an application scenario of a driving assistance method provided by an embodiment of the present application.

FIG. 6 is another schematic diagram of an application scenario of a driving assistance method provided by an embodiment of the present application.

FIG. 7 is another schematic diagram of an application scenario of a driving assistance method provided by an embodiment of the present application.

FIG. 8 is another schematic flow chart of a driving assistance method provided by an embodiment of the present application.

FIG. 9 is a schematic block diagram of a driving assistance device provided by an embodiment of the present application.

Figure 10 is another schematic block diagram of a driving assistance device provided by an embodiment of the present application.

Detailed ways

The technical solutions in the embodiments of the present application will be described below with reference to the drawings in the embodiments of the present application. Among them, in the description of the embodiments of this application, unless otherwise stated, "/" means or, for example, A/B can mean A or B; "and/or" in this article is only a way to describe related objects. The association relationship means that there can be three relationships. For example, A and/or B can mean: A alone exists, A and B exist simultaneously, and B alone exists.

Prefixes such as "first" and "second" are used in the embodiments of this application only to distinguish different description objects, and have no limiting effect on the position, order, priority, quantity or content of the described objects. In the embodiments of this application, the use of ordinal words and other prefixes used to distinguish the described objects does not limit the described objects. For the statement of the described objects, please refer to the claims or the context description in the embodiments. The use of such prefixes should not be used. Words constitute redundant restrictions. Furthermore, in the description of this embodiment, unless otherwise specified, "plurality" means two or more.

FIG. 1 is a functional block diagram of a vehicle 100 provided by an embodiment of the present application. The vehicle 100 may include a perception system 120 , a display device 130 , and a computing platform 150 , where the perception system 120 may include several types of sensors that sense information about the environment surrounding the vehicle 100 . For example, the sensing system 120 may include a positioning system. The positioning system may be a global positioning system (GPS), a Beidou system or other positioning systems, an inertial measurement unit (IMU), a lidar, a millimeter One or more of wave radar, ultrasonic radar and camera device.

Some or all functions of vehicle 100 may be controlled by computing platform 150 . The computing platform 150 may include processors 151 to 15n (n is a positive integer). The processor is a circuit with signal processing capabilities. In one implementation, the processor may be a circuit with instruction reading and execution capabilities. For example, central processing unit (CPU), microprocessor, graphics processing unit (GPU) (can be understood as a microprocessor), or digital signal processor (DSP), etc. ; In another implementation, the processor can realize certain functions through the logical relationship of the hardware circuit. The logical relationship of the hardware circuit is fixed or can be reconstructed. For example, the processor is an application-specific integrated circuit (application-specific integrated circuit). ASIC) or programmable logic device (PLD) implemented hardware circuit, such as field programmable logic gate array (field programmable gate array, FPGA). In a reconfigurable hardware circuit, the process of the processor loading the configuration file and realizing the hardware circuit configuration can be understood as the process of the processor loading instructions to realize the functions of some or all of the above units. In addition, it can also be a hardware circuit designed for artificial intelligence, which can be understood as an ASIC, such as a neural network processing unit (NPU), tensor processing unit (TPU), deep learning processing Unit (deep learning processing unit, DPU), etc. In addition, the computing platform 150 may also include a memory, which is used to store instructions. Some or all of the processors 151 to 15n may call instructions in the memory and execute the instructions to implement corresponding functions.

The display device 130 in the cockpit is mainly divided into two categories. The first category is a vehicle-mounted display screen; the second category is a projection display screen, such as a head-up display (HUD). The vehicle display screen is a physical display screen and an important part of the vehicle infotainment system. There can be multiple displays in the cockpit, such as digital instrument display, central control screen, passenger in the co-pilot seat (also known as The display in front of the front passenger), the display in front of the left rear passenger, the display in front of the right rear passenger, and even the car window can be used as a display. Head-up display, also known as head-up display system. It is mainly used to display driving information such as speed and navigation on the display device in front of the driver (such as the windshield). This reduces the driver's gaze shift time, avoids pupil changes caused by the driver's gaze shift, and improves driving safety and comfort. HUD includes, for example, combined head-up display (combiner-HUD, C-HUD) system, windshield-type head-up display (windshield-HUD, W-HUD) system, and augmented reality head-up display system (augmented reality HUD, AR-HUD). In some possible implementations, the vehicle display screen may include an HMI.

As mentioned above, most traffic violations are caused by incorrect driving habits. In the process of a driver changing from a novice to a skilled driver, without support and assistance from the driver, it is difficult to learn skills and form good driving habits and maintain them. . In the whole driving scene, there is a lack of adaptive reminder mechanism for drivers with different driving habits and familiarity with the vehicle. In view of this, embodiments of the present application provide a driving assistance method, device and vehicle, which can obtain the driver's driving data in real time, and determine whether to perform driving reminders based on the driving data, combined with vehicle surrounding environment information and/or vehicle driving status data. Determining the content of the reminder can help drivers with poor driving habits and/or insufficient driving experience learn and/or consolidate their driving experience, improve the driver's driving experience, and also help improve driving safety.

Figure 2 shows a system architecture diagram of assisted driving provided by an embodiment of the present application. As shown in Figure 2, the assisted driving system includes a driving virtual assistant unit, which includes a learning unit, a user interaction module, a control module, a data management module and a data acquisition module. The data acquisition module may include one or more camera devices in the sensing system 120 shown in Figure 1, and one or more sensors; the data management module may include one of the computing platforms 150 shown in Figure 1 or multiple memories; the user interaction module may include one or more of the display devices 130 in Figure 1 , and the user interaction module may also include a voice system; the control module may include one or more of the computing platforms 150 shown in Figure 1 processor; the learning unit may include one or more processors in the computing platform 150 shown in FIG. 1 , and more specifically, the learning unit may include a learning application unit and a learning method unit. During the specific implementation process, the data acquisition module can obtain the driver's driving data, including acceleration data (such as acceleration rate, gas pedal position, number of acceleration adjustments), deceleration data (such as deceleration rate, brake opening) brake pedal position), steering data (such as steering wheel angle, turning rate), manual parking time, etc. The data management module can process driving data, such as calculating the driver's average manual parking time, etc. The data management module can also store the data obtained by the data acquisition module. Further, the learning application unit can determine the driver's driving experience and driving habits based on the driving data, the data processed by the data management module, and the algorithm stored in the learning method unit. In addition, the data acquisition module can also obtain the vehicle's surrounding environment information, where the vehicle's surrounding environment information includes but is not limited to: road information (such as congestion, pedestrians around, curves, traffic signs, etc.), surrounding vehicle information (such as the relationship with the vehicle in front) distance). The learning unit can determine whether to provide a driving reminder and the content of the driving reminder based on the vehicle surrounding environment information and/or vehicle driving status data in the data acquisition module, combined with the driver's driving experience and driving habits. When a driving reminder is required, the learning unit sends an instruction to the control module, so that the control module can control the user interaction module to provide a driving reminder. Among them, driving reminders include at least one of the following: speed reminders, road right reminders, driving observation reminders, vehicle distance reminders, temporary/prohibited parking reminders, and other illegal and illegal driving behavior reminders.

In some possible implementations, the assisted driving system also includes an automatic driving (advanced driver assistance system, ADAS) unit, which is connected to one or more sensors in the perception system shown in Figure 1. The driving virtual assistant The unit can obtain driving data and vehicle surrounding environment information from the autonomous driving unit. In some possible implementations, control instructions can also be sent to the automatic driving unit through the control module in the driving virtual assistant unit, so that the automatic driving unit can provide driving reminders.

It should be understood that the above modules and systems are only examples. In actual applications, the above modules and systems may be added or deleted according to actual needs. For example, the data management module and the data processing module can be combined into one module, or the learning unit and the control module can also be combined into one module.

FIG. 3 shows a schematic flowchart of a driving assistance method provided by an embodiment of the present application. The method 300 may be applied to the vehicle shown in FIG. 1 , or may be executed by the system shown in FIG. 2 . It should be understood that the steps or operations of the assisted driving method shown in FIG. 3 are only exemplary, and the embodiments of the present application may also perform other operations or modifications of each operation in FIG. 3 . The method 300 includes:

S301, obtain the driver's driving data.

For example, acceleration data, such as acceleration, throttle opening, etc., deceleration data, such as deceleration, brake opening, etc., steering data, such as steering wheel angle, turning rate, etc., and manual parking time and other data are obtained.

For example, the moment when the driver's driving data is started to be acquired may be the moment when the driver starts the vehicle. For example, the driving data may include driving data of the current trip. More specifically, the driving data may include driving data obtained from the time the driver starts the vehicle during the current trip, or may also include driving data from the first moment of the trip. According to the acquired driving data, the first time is the time when the current time is moved forward by a preset time. For example, the preset time can be 20 minutes (minutes, min), or it can be 40 minutes, or it can also be Other durations.

S302, determine the driver's driving experience and driving habits.

In the embodiment of this application, driving experience and driving habits are used to characterize the driver's driving behavior. Among them, driving experience represents the driver's proficiency in driving a vehicle and/or the length of driving experience, and driving habits are used to represent the driving behavior or driving tendency that the driver has gradually developed during long-term driving activities and is not easy to change for a while. It should be understood that a driver with rich driving experience may not necessarily have good driving habits, and a driver with excellent driving habits may not necessarily have rich driving experience.

In some possible line-of-sight methods, the driver's driving experience and driving habits can be determined based on the driver's driving data and the surrounding environment information during vehicle driving.

As an example, the driver's driving experience can be determined based on the duration of manual parking. For example, according to the parking space type, the time interval required for parking in this type of parking space is determined. Furthermore, if the parking time in the current trip is within the first x% of the time interval required for parking in this type of parking space, it is determined that the driver has rich driving experience; otherwise, it is determined that the driver has insufficient driving experience. For example, x can be 50, or it can be 60, or it can be any real number between 0 and 100.

As another example, the deceleration, acceleration and steering data in the driving data are compared with the corresponding Gaussian model to determine the driver's driving experience.

For example, taking deceleration data as an example, the driver's driving experience can be determined based on the deceleration and braking duration. Specifically, the Gaussian distribution of deceleration data can be determined according to the following formula:

Among them, x is the deceleration data, including deceleration rate (Deceleration rate) and braking duration (Brake duration), μ is the mean value, and Σ is the covariance matrix. Specifically, μ=[μ _{Decelerationrate} ,μ _{Brakeduration} ],

σ is the standard deviation and σ ² is the variance.

Further, a deceleration Gaussian model as shown in Figure 4 can be established, where the upper ellipse in Figure 4 represents a driver who lacks driving experience (such as a novice driver), and the lower ellipse represents a driver with rich driving experience. Then compare the deceleration data in the driving data with the Gaussian model shown in Figure 4. If the deceleration data falls within the upper ellipse, it means that the driver lacks driving experience. If the deceleration data falls within the lower ellipse, it means that the driver is driving. More experienced.

In some possible implementations, if there are multiple sets of deceleration data in the driving data of the current trip, each set of deceleration data in the multiple sets of deceleration data will be judged separately, and then the judgment results of each set of deceleration data will be combined to determine the driving driver’s driving experience. For example, if more than 80% of the deceleration data falls within the upper ellipse, the driver is deemed to have insufficient driving experience; if more than 80% of the deceleration data falls within the lower ellipse, the driver is deemed to have insufficient driving experience. relatively rich.

It should be understood that the acceleration Gaussian model can also be used in combination with acceleration data to determine the driver's driving experience, and the steering Gaussian model can be used in combination with steering data to determine the driver's driving experience.

In some possible implementations, when the driving data of the current trip includes acceleration data, deceleration data and steering data at the same time, the result A judged based on the acceleration data, the result D judged based on the deceleration data and the result D judged based on the steering data can be The judgment result T is combined to determine the driver's driving experience. Among them, A, D, and T can take 0 or 1 respectively. When taking 1, it means that the judgment result is "the driver has rich driving experience", and when taking 0, it means "the driver has insufficient driving experience". For example, the final result of the driving experience E ₁ =a*A+b*D+c*T, where a, b, and c are respectively the result A judged based on the acceleration data, the result D judged based on the deceleration data, and the result D judged based on the deceleration data. Turn to the weight of the result T of data judgment. For example, a, b, and c can be 0.4, 0.3, and 0.3 respectively. Then when E ₁ is greater than or equal to 0.6, it is determined that the driver has rich driving experience. It should be understood that a, b, and c can also take other real numbers, and the judgment conditions can also change with the value of the weight, which is not specifically limited in this application.

In some possible implementations, the final result of driving experience E ₂ =a*A+b*D+c*T+d*P, where P is the result judged based on the parking duration, and P can be respectively 0 or 1. When it is set to 1, it means that the judgment result is "the driver has rich driving experience", and when it is set to 0, it means "the driver has insufficient driving experience". d is the weight of the result judged based on the parking time. For example, a, b, c, and d can be 0.4, 0.3, 0.2, and 0.1 respectively. Then when E ₂ is greater than or equal to 0.5, it is determined that the driver has rich driving experience.

In some possible implementations, the driver's driving experience can also be determined based on at least one of acceleration smoothness (acceleration smoothness), deceleration smoothness (deceleration smoothness), and turning smoothness (turning smoothness). For example, the value range of the acceleration smoothness (or deceleration smoothness, or steering smoothness) of historical passing vehicles on the road segment that the vehicle is currently traveling on is determined. Furthermore, if the acceleration smoothness (or deceleration smoothness, or steering smoothness) of the own vehicle during this trip is within the first y% of the value range of the acceleration smoothness on the current road section, it is determined that the driver has rich driving experience. Otherwise, it is determined that the driver has insufficient driving experience. For example, x can be 50, or it can be 60, or it can be any real number between 0 and 100. For example, the driver's driving experience can also be determined based on the acceleration smoothness, deceleration smoothness and steering smoothness. For example, the deceleration smoothness calculation formula can be: DS=λs(Mm|T), where Mm is the brake opening, T is the duration of the braking action, and λs is the smoothness equation. It should be understood that the acceleration smoothness and steering smoothness can also be calculated with reference to the above formula.

In some possible implementations, the current driver's driving habits can be characterized by a driving habit score Score _(Driving _Habits) . For example, Score _{(Driving Habits)} =a ₁₊ a ₂₊ a ₃₊ a ₄₊ a ₅ . Among them, a ₁ to a ₅ respectively represent the weight of vehicle speed, yield, distance between vehicles, temporary parking, and traffic regulations, as shown in Table 1. The values of a ₁ to a ₅ can be any real number between 0 and 1. For example, in the current trip, when any of the overspeeding, sharp turning ratio is greater than 0.5, and sudden braking ratio is greater than 0.5, a ₁ takes 0, otherwise a ₁ takes 1; when a specific event occurs in the current trip When the road section does not give way, a ₂ takes 0, otherwise a ₂ takes 1; when the proportion of following cars too close is greater than 0.5 in the current trip, a ₃ takes 0, otherwise a ₃ takes 1; in the current trip, if If a temporary parking occurs and blocks road traffic, a ₄ will be taken as 0, otherwise a ₄ will be taken as 1; during the current trip, if a violation of traffic regulations occurs, such as failure to follow lane lines, knowledge lights and signs, etc., then a ₅ will be taken as 0, Otherwise a ₅ takes 1. Furthermore, when Score _{(Driving Habits)} is greater than A, the driver's driving habits are good; when Score _{(Driving Habits)} is less than or equal to A, the driver's driving habits need to be improved, where A is the good driving habit score. For example, A may be 3 or 4, or may be other values from 0 to 5.

Table 1 Driver’s driving behavior and the weight of driving behavior in driving habit scores

In some possible implementations, when there are one or more fixed drivers of the vehicle, the driver's driving experience and driving habits can also be determined in combination with driver profiles. Furthermore, when determining driving habits, the driving habit score can be Score _{(Driving Habits)} =a ₁₊ a ₂₊ a ₃₊ a ₄₊ a ₅₊ a ₆ , where a ₆ is the weight of other driving behaviors, such as FCW, the number of forced exits of intelligent driving, when the number of front collision warnings and/or the number of forced exits of intelligent driving exceed the preset threshold, then a ₆ takes 0, otherwise a ₆ takes 1.

In some possible implementations, when there are one or more fixed drivers of the vehicle, the irregular driving behavior of each driver can also be counted separately within the preset trip. For example, for the driver A, record the number of times they speeded, failed to yield, followed too closely, made wrong temporary stops, and violated traffic regulations. For example, the preset stroke may be 500km, or 1000km, or other values.

S303, determine whether the driver has rich driving experience and good driving habits.

Specifically, when the driver has rich driving experience and good driving habits are not established, S304 is executed; otherwise, S305 is executed.

It should be understood that "the driver has rich driving experience and good driving habits is not true" includes: the driver has rich driving experience but poor driving habits; the driver has good driving habits but lacks driving experience; the driver has insufficient driving experience and Poor driving habits.

S304, perform driving reminders and/or driving recommendations.

For example, vehicle surrounding environment information is obtained, and the content and timing of driving reminders and/or driving recommendations are determined based on the vehicle surrounding environment information. In some possible implementations, speed reminders and/or recommendations, right-of-way reminders and/or recommendations, driving observation reminders and/or recommendations, vehicle distance reminders and/or recommendations, temporary/prohibited parking reminders and/or recommendations can be performed. , reminders of other illegal driving behaviors.

For example, driving reminders and/or driving recommendations can be made through display devices such as central control screens, or driving reminders and/or driving recommendations can be made through voice broadcasts, or through human-computer interaction interfaces such as HMI. etc. to perform driving reminders and/or driving recommendations, which are not specifically limited in the embodiments of this application.

One example is to remind the driver of driving observations and/or recommended vehicle speeds based on road risk and braking distance. For example, in low-visibility weather conditions such as rain, snow, fog, etc., driving reminders and/or driving recommendations are provided, such as reminding the driver to reduce the speed, or reminding the driver of the recommended vehicle speed, such as broadcasting reminders through display devices and/or voice. "It is recommended that the vehicle speed does not exceed 20km/h"; when the road is congested, there are pedestrians around, curves, etc., the driver is reminded to reduce the speed, or the recommended speed is reminded; when the driver is about to merge into the main road, the driver is reminded of the recommended speed route and speed. In some possible implementations, the driver can also be prompted to turn on intelligent driving. In the above scenario, the driver can also be reminded of the recommended throttle amplitude and frequency, as well as braking amplitude and frequency and other information through the display device and/or voice broadcast. As shown in Figure 5, when a vehicle passes through a road section with multiple parked vehicles on one side, drivers with inexperienced driving and/or poor driving habits can be reminded and given a recommended speed to prevent pedestrians from suddenly crossing. causing accidents. As shown in (a) in Figure 5, the current driving speed of the vehicle is 40km/h. When multiple parked vehicles are detected on the left side, and pedestrians may pass through the parked vehicles, the central control unit can The screen prompts "Please control the speed and pay attention to the vehicle on the left to prevent pedestrians from crossing." At the same time, the recommended speed can also be prompted on the central control screen

In some possible implementations, it can be displayed by flashing

Increase the visibility of recommended speeds. In some possible implementations, driving suggestions can also be provided by combining vibrations of steering wheels, seat belts, seats and other equipment, and/or flashing of breathing lights (or ambient lights) in the car, to make driving suggestions more attractive to the driver. attention.

In some possible implementations, when it is determined that the driver has insufficient driving experience and/or has poor driving habits, the driver can also be advised to turn on smart driving through the central control screen. As shown in (b) in Figure 5, the central control screen displays "The current road section supports smart driving, is it enabled?". The driver can confirm that smart driving is enabled by clicking the "Yes" button on the screen, or, alternatively, You can click the "No" button on the screen to not enable smart driving. Further, after smart driving is turned on in response to the driver's click operation, the vehicle's automatic driving module takes over the vehicle, controls the vehicle's driving speed to drop to 20km/h, and prompts the driver through the screen that "smart driving has been turned on", as shown in the figure. As shown in (c) in 5.

In some possible implementations, the above recommended vehicle speed can be sensed and controlled by the autonomous driving system, or it can be received through vehicle to roadside infrastructure (V2I) communication, or it can also be received through other means. The way is determined. Furthermore, the accelerator amplitude and frequency of the reminder, as well as the braking amplitude and frequency, etc. can be calculated based on the recommended vehicle speed, or can also be determined through other methods.

Another example, prompting the driver to yield on a specific road section. For example, give way to pedestrians in schools, residential areas and villages, give way to pedestrians, bicycles and motorcycles in rainy and snowy days, turn right to left at intersections, give way at intersections without signal lights, give way at roundabouts, give way when entering the main road, give way on ramps, follow the traffic rules Give way to signs and markings, give way to overtaken vehicles, and give way to special vehicles (police cars, fire trucks, ambulances, engineering rescue vehicles and school buses). As shown in (a) in Figure 6, when driving to an intersection without signal lights and detecting a vehicle traveling from left to right at the intersection, for drivers with inexperienced driving and/or poor driving habits, you can do the following: The reminder "Please give way to the vehicle on the left" shown in (b) in Figure 6; for drivers with rich driving experience and good driving habits, they do not need to be reminded, and the central control screen displays as shown in Figure 6 (( The screen shown in c).

In some possible implementations, the location of other road users can be obtained through the vehicle sensing system, or can be determined through information received by V2I, or it can also be through vehicle-to-vehicle communication (V2V). ) is determined by the information received, or it can be determined by other means.

Another example is that in restricted parking areas, such as railway stations and airport terminal curbs, the parking duration is prompted. If the lane is blocked, a reminder is given and an automatic adjustment option is given; when parking on a slope, turn the front wheels to prevent slipping. vehicles; no parking areas (according to traffic laws), reminders and suggestions for surrounding parking lots and parking spaces.

In some possible implementations, information such as parking duration, recommended surrounding parking length and parking spaces can be determined through information received by V2I, or it can also be determined through vehicle to everything (V2X) information exchange. The information received may be determined by other means.

As another example, based on the risk of road conditions and braking distance, low visibility weather such as rain, snow and fog, congestion, pedestrians around, and curves, it is recommended to keep distance between vehicles; when encountering other road users, such as large vehicles, parked vehicles, and bicycles , motorcycles, school buses and pedestrians, etc., please keep a distance between vehicles.

In some possible implementations, the recommended distance between vehicles can be preset by the system. For example, the recommended distance between vehicles can be set separately for different scenarios such as rain, snow, fog, low visibility weather, congestion, pedestrians around, curves, etc.; or , the recommended distance between vehicles can also be determined based on other methods.

In some possible implementations, when a vehicle has one or more fixed drivers, and the driver profile is used to determine the driver's driving experience and driving habits, personalized reminders can also be provided for different drivers. . For example, driver A is a driver with inexperience and/or poor driving behavior, but within the preset trip (such as 1000km, or other), driver A has never failed to give way on a specific road section, then There is no need to remind you on the road sections where you need to give way.

S305, no driving reminder and/or driving recommendation is performed.

For example, when it is determined that the driver has rich driving experience and good driving habits, driving reminders may not be provided during driving to save energy consumption.

In some possible implementations, the assisted driving method provided by the embodiments of the present application can also count the types and/or occurrence times of irregular driving behaviors during each trip, and provide a trip summary and reminder. For example, during a trip, poor driving behaviors include "failure to yield at intersections", "failure to keep a distance from large vehicles", and "illegal parking", and the number of times the above behaviors occurred were 3, 4, and 4 times respectively. 3 times. After the trip ends, the reminder information shown in (a) in Figure 7 is displayed to help the driver understand his driving performance and deepen his impression. Optionally, it can also be compared with the number of bad driving behaviors recorded in the historical itinerary, and then the driver can be reminded of the changes in irregular driving behavior compared with the historical itinerary (such as "5 items have been improved compared to the last time") , to promote the development of good driving habits and maintain vigilance for safe driving. If there is no bad driving behavior during the trip, only the trip route can be displayed, or the number of times the driver has completed zero-risk trips can be displayed to encourage the driver to continue to maintain good driving habits. For example, the content shown in (b) in Figure 7 can be displayed, "A very smooth trip, 0 risk events and 10 safe trips have been completed in a row, please keep it up!". It should be understood that the above information can also be prompted to the driver through voice broadcast or other means.

In the embodiments of this application, terms such as "relatively rich", "good", "insufficient", and "poor" are introduced for the convenience of understanding and explanation, and should not constitute any limitation to this application.

The driving assistance method provided by the embodiment of the present application can obtain the driver's driving data in real time, determine whether to provide a driving reminder based on the driving data, and determine the content of the reminder based on the vehicle's surrounding environment information and/or vehicle driving status data. Help drivers with poor driving habits and/or insufficient driving experience learn and/or consolidate their driving experience, improve the driver's driving experience, and also help improve driving safety. Especially in the field of shared cars, the drivers who use a certain vehicle may be different each time, and their driving experience and driving habits are also uneven. In this case, obtaining driving data in real time and determining the driver's driving experience and driving habits, and then providing driving reminders, can help improve driving safety.

FIG. 8 shows a schematic flowchart of a driving assistance method 800 provided by an embodiment of the present application. The method 800 may be applied to the vehicle shown in FIG. 1 , or may be executed by the system shown in FIG. 2 . It should be understood that the steps or operations of the assisted driving method shown in FIG. 8 are only exemplary, and the embodiment of the present application may also perform other operations or modifications of each operation in FIG. 8 . The method 800 includes:

S801: Obtain the real-time driving parameters of the driver when driving the vehicle and the surrounding environment information of the vehicle.

Illustratively, the vehicle may be the vehicle 100 in the above embodiment, or may be another vehicle; the real-time driving data may include the driving data in the above embodiment, or may include the vehicle driving status data in the above embodiment, or It may also include vehicle driving parameters when other drivers drive the vehicle; the surrounding environment information may be the vehicle surrounding environment information in the above embodiment, or may also include other environment information around the vehicle during vehicle driving.

For the method of obtaining the real-time driving parameters and the surrounding environment information, reference can be made to the description in the above embodiments, which will not be described again here.

S802: Determine the driver's driving habits based on the real-time driving parameters and the surrounding environment information.

For example, the driving habits may include the driving habits described in the above embodiments. The method of determining the driver's driving habits based on the real-time driving parameters and the surrounding environment information may refer to the description in the above embodiments, which will not be described here. Repeat.

S803: When the driving habit meets the first preset condition, prompt the driver with driving reminder information.

For example, the first preset condition may include that the driving habit score Score _{(Driving Habits)} in the above embodiment is less than the good driving habit score, or may be other conditions that can characterize the driver's poor driving habits.

The driving reminder information may include the driving reminder and/or driving recommendation in the above embodiment, or may also include the speed reminder, road right reminder, driving observation reminder, vehicle distance reminder, temporary/prohibited parking reminder, and other illegal violations in the above embodiment. At least one of the driving violation reminders. More specifically, for the method of prompting the driver with driving reminder information, reference may be made to the description in the above embodiments, which will not be described again here.

In the above technical solution, the driver's driving habits can be determined based on the vehicle driving parameters and the vehicle's surrounding environment information obtained in real time when the driver drives the vehicle. Furthermore, it can be determined based on the driver's driving habits whether the vehicle is driving. Driving reminders can help drivers with poor driving habits learn and/or consolidate what they need to pay attention to during driving, help drivers develop good driving habits, and also help improve driving safety.

In the various embodiments of this application, if there is no special explanation or logical conflict, the terms and/or descriptions between the various embodiments are consistent and can be referenced to each other. The technical features in different embodiments are based on their inherent logic. Relationships can be combined to form new embodiments.

The method provided by the embodiment of the present application is described in detail above with reference to FIGS. 3 to 8 . The device provided by the embodiment of the present application will be described in detail below with reference to Figures 9 and 10. The description of the device embodiments corresponds to the description of the method embodiments. Therefore, for content that is not described in detail, please refer to the above method embodiments. For the sake of brevity, they will not be described again here.

FIG. 9 shows a schematic block diagram of a driving assistance device 2000 provided by an embodiment of the present application. The device 2000 includes an acquisition unit 2010, a processing unit 2020, and a prompting unit 2030. The acquisition unit 2010 can implement corresponding communication functions, the processing unit 2020 is used for data processing, and the prompting unit 2030 is used to prompt driving reminder information to the driver.

Optionally, the device 2000 may also include a storage unit, which may be used to store instructions and/or data, and the processing unit 2020 may read the instructions and/or data in the storage unit, so that the device implements the foregoing method embodiments. .

The apparatus 2000 may include units for performing the method in FIG. 3 or FIG. 8 . Moreover, each unit in the device 2000 and the above-mentioned other operations and/or functions are respectively intended to implement the corresponding processes of the method embodiment of FIG. 3 or FIG. 8 .

Wherein, when the device 2000 is used to execute the method 800 in Figure 8, the acquisition unit 2010 can be used to execute S801 in the method 800, the processing unit 2020 can be used to execute S802 in the method 800, and the prompting unit 2030 can be used to execute the method 800. S803.

Specifically, the device 2000 includes: an acquisition unit 2010, used to acquire the real-time driving parameters when the driver drives the vehicle and the surrounding environment information of the vehicle; and a processing unit 2020, used to determine the real-time driving parameters and the surrounding environment information based on the real-time driving parameters and the surrounding environment information. The driver's driving habits; the prompt unit 2030 is used to prompt the driver with driving reminder information when the driving habits meet the first preset condition.

In some possible implementations, the processing unit 2020 is also configured to: determine the driver's driving experience according to the real-time driving parameters; the prompting unit 2030 is specifically configured to: when the driving habit satisfies the first preset condition, and when When the driving experience meets the second preset condition, the driving reminder information is prompted to the driver.

In some possible implementations, the prompt unit 2030 is also configured to: when detecting that the vehicle speed exceeds the preset speed, prompt the driver with vehicle speed reminder information, and the vehicle speed reminder information is used to remind the driver to decelerate and/or recommend vehicle speed; and/or when detecting other road users, prompt the driver with yield indication information, which is used to remind the driver to give way to other road users; and/or between the vehicle and the vehicle in front When the distance between vehicles is less than or equal to the preset distance, a vehicle distance reminder message is prompted to the driver. The vehicle distance reminder message is used to remind the driver to maintain the vehicle distance and/or the recommended vehicle distance; and/or when the vehicle is detected to enter the restriction. When parking in a parking area, a temporary parking reminder message is prompted to the driver. The temporary parking reminder message is used to remind the restricted parking area and/or parking duration; and/or when the vehicle is detected to change lanes, slow down, or there are other vehicles behind the vehicle. When there is at least one obstacle in the vehicle or the driving road, a driving observation reminder message is prompted to the driver. The driving observation reminder information is used to prompt the driver to observe the violation reminder information around the vehicle.

In some possible implementations, the prompt unit 2030 is also configured to: at the end of the current trip, prompt the data of irregular driving that occurred in the current trip, and/or prompt the data of irregular driving that occurred in the current trip. Comparison results with data on irregular driving that occurred during historical trips.

In some possible implementations, the irregular driving includes the distance between the vehicle and the vehicle in front being less than or equal to the preset distance, failure to give way to other road users, illegal parking, speeding, and violating at least one of the traffic rules. One item.

In some possible implementations, when the vehicle travels to the first road section and the first road section supports intelligent driving, the prompt unit 2030 is also used to prompt the driver to switch the vehicle to the intelligent driving mode.

In some possible implementations, the processing unit 2020 is also configured to determine the driving reminder information based on the surrounding environment information before the prompting unit 2030 prompts the driver with the driving reminder information.

In some possible implementations, the real-time driving parameters include a yielding parameter, which is used to characterize the vehicle's behavior of yielding to other road users during the current trip.

It should be understood that the division of each unit in the above device is only a division of logical functions. In actual implementation, the units may be fully or partially integrated into a physical entity, or may be physically separated. In addition, the unit in the device can be implemented in the form of a processor calling software; for example, the device includes a processor, the processor is connected to a memory, instructions are stored in the memory, and the processor calls the instructions stored in the memory to implement any of the above methods. Or realize the functions of each unit of the device, where the processor is, for example, a general-purpose processor, such as a CPU or a microprocessor, and the memory is a memory within the device or a memory outside the device. Alternatively, the units in the device can be implemented in the form of hardware circuits, and some or all of the functions of the units can be implemented through the design of the hardware circuits, which can be understood as one or more processors; for example, in one implementation, The hardware circuit is an ASIC, which realizes the functions of some or all of the above units through the design of the logical relationship of the components in the circuit; for another example, in another implementation, the hardware circuit can be implemented through PLD, taking FPGA as an example. It can include a large number of logic gate circuits, and the connection relationships between the logic gate circuits can be configured through configuration files to realize the functions of some or all of the above units. All units of the above device may be fully realized by the processor calling software, or may be fully realized by hardware circuits, or part of the units may be realized by the processor calling software, and the remaining part may be realized by hardware circuits.

In the embodiment of the present application, the processor is a circuit with signal processing capabilities. In one implementation, the processor may be a circuit with instruction reading and execution capabilities, such as a CPU, a microprocessor, a GPU, or DSP, etc.; in another implementation, the processor can realize certain functions through the logical relationship of the hardware circuit. The logical relationship of the hardware circuit is fixed or can be reconstructed. For example, the processor is a hardware circuit implemented by ASIC or PLD. For example, FPGA. In a reconfigurable hardware circuit, the process of the processor loading the configuration file and realizing the hardware circuit configuration can be understood as the process of the processor loading instructions to realize the functions of some or all of the above units. In addition, it can also be a hardware circuit designed for artificial intelligence, which can be understood as an ASIC, such as NPU, TPU, DPU, etc.

It can be seen that each unit in the above device can be one or more processors (or processing circuits) configured to implement the above method, such as: CPU, GPU, NPU, TPU, DPU, microprocessor, DSP, ASIC, FPGA , or a combination of at least two of these processor forms.

In addition, each unit in the above device may be integrated together in whole or in part, or may be implemented independently. In one implementation, these units are integrated together and implemented as a system-on-a-chip (SOC). The SOC may include at least one processor for implementing any of the above methods or implementing the functions of each unit of the device. The at least one processor may be of different types, such as a CPU and an FPGA, or a CPU and an artificial intelligence processor. CPU and GPU etc.

Figure 10 is a schematic block diagram of a driving assistance device according to an embodiment of the present application. The driving assistance device 2100 shown in FIG. 10 may include: a processor 2110, a transceiver 2120, and a memory 2130. Among them, the processor 2110, the transceiver 2120 and the memory 2130 are connected through an internal connection path. The memory 2130 is used to store instructions. The processor 2110 is used to execute the instructions stored in the memory 2130, and the transceiver 2120 receives/sends some parameters. Optionally, the memory 2130 can be coupled with the processor 2110 through an interface or integrated with the processor 2110 .

It should be noted that the above-mentioned transceiver 2120 may include but is not limited to a transceiver device such as an input/output interface to realize communication between the device 2100 and other devices or communication networks.

During the implementation process, each step of the above method can be completed by instructions in the form of hardware integrated logic circuits or software in the processor 2110 . The methods disclosed in conjunction with the embodiments of the present application can be directly implemented as executed by a hardware processor, or executed using a combination of hardware and software modules in the processor. The software module can be located in random access memory, flash memory, read-only memory, programmable read-only memory or electrically erasable programmable memory, registers and other mature storage media in this field. The storage medium is located in the memory 2130. The processor 2110 reads the information in the memory 2130 and completes the steps of the above method in combination with its hardware. To avoid repetition, it will not be described in detail here.

The processor 2110 may use a general-purpose CPU, microprocessor, ASIC, GPU or one or more integrated circuits to execute relevant programs to implement the assisted driving method of the method embodiment of the present application. The processor 2110 may also be an integrated circuit chip with signal processing capabilities. In a specific implementation process, each step of the assisted driving method of the present application can be completed by instructions in the form of hardware integrated logic circuits or software in the processor 2110 . The above-mentioned processor 2110 can also be a general-purpose processor, DSP, ASIC, FPGA or other programmable logic device, discrete gate or transistor logic device, or discrete hardware component. Each method, step and logical block diagram disclosed in the embodiment of this application can be implemented or executed. A general-purpose processor may be a microprocessor or the processor may be any conventional processor, etc. The steps of the method disclosed in conjunction with the embodiments of the present application can be directly implemented by a hardware decoding processor, or executed by a combination of hardware and software modules in the decoding processor. The software module can be located in random access memory, flash memory, read-only memory, programmable read-only memory or electrically erasable programmable memory, registers and other mature storage media in this field. The storage medium is located in the memory 2130. The processor 2110 reads the information in the memory 2130 and executes the assisted driving method of the method embodiment of the present application in conjunction with its hardware.

The memory 2130 may be a read-only memory (ROM), a static storage device, a dynamic storage device or a random access memory (RAM).

The transceiver 2120 uses a transceiver device such as but not limited to a transceiver to implement communication between the device 2100 and other devices or communication networks.

Embodiments of the present application also provide a driving assistant, which includes at least one of a virtual image and a physical image. The driving assistant includes at least one processor for executing a computer program stored in a memory, so that the driving The assistant performs the method in Figure 3 or Figure 8; the driving assistant can be carried on at least one of a vehicle screen, a head-up display HUD, a cockpit, and a vehicle voice device.

An embodiment of the present application also provides a driving assistance system, which includes the above device 2000 or the above device 2100.

An embodiment of the present application also provides an intelligent vehicle, which may include the above device 2000 or the above device 2100.

Embodiments of the present application also provide a computer-readable medium. The computer-readable medium stores program code. When the computer program code is run on a computer, it causes the computer to execute the method in Figure 3 or Figure 8. .

An embodiment of the present application further provides a chip, including: at least one processor and a memory, the at least one processor being coupled to the memory and configured to read and execute instructions in the memory to execute the above-mentioned Figure 3 or Method in Figure 8.

It should be understood that in the various embodiments of the present application, the size of the sequence numbers of the above-mentioned processes does not mean the order of execution. The execution order of each process should be determined by its functions and internal logic, and should not be used in the embodiments of the present application. The implementation process constitutes any limitation.

Those of ordinary skill in the art will appreciate that the units and algorithm steps of each example described in conjunction with the embodiments disclosed herein can be implemented with electronic hardware, or a combination of computer software and electronic hardware. Whether these functions are performed in hardware or software depends on the specific application and design constraints of the technical solution. Skilled artisans may implement the described functionality using different methods for each specific application, but such implementations should not be considered beyond the scope of this application.

Those skilled in the art can clearly understand that for the convenience and simplicity of description, the specific working processes of the systems, devices and units described above can be referred to the corresponding processes in the foregoing method embodiments, and will not be described again here.

In the several embodiments provided in this application, it should be understood that the disclosed systems, devices and methods can be implemented in other ways. For example, the device embodiments described above are only illustrative. For example, the division of the units is only a logical function division. In actual implementation, there may be other division methods. For example, multiple units or components may be combined or can be integrated into another system, or some features can be ignored, or not implemented. On the other hand, the coupling or direct coupling or communication connection between each other shown or discussed may be through some interfaces, and the indirect coupling or communication connection of the devices or units may be in electrical, mechanical or other forms.

The units described as separate components may or may not be physically separated, and the components shown as units may or may not be physical units, that is, they may be located in one place, or they may be distributed to multiple network units. Some or all of the units can be selected according to actual needs to achieve the purpose of the solution of this embodiment.

In addition, each functional unit in each embodiment of the present application can be integrated into one processing unit, each unit can exist physically alone, or two or more units can be integrated into one unit.

If the functions are implemented in the form of software functional units and sold or used as independent products, they can be stored in a computer-readable storage medium. Based on this understanding, the technical solution of the present application is essentially or the part that contributes to the existing technology or the part of the technical solution can be embodied in the form of a software product. The computer software product is stored in a storage medium, including Several instructions are used to cause a computer device (which may be a personal computer, a server, or a network device, etc.) to execute all or part of the steps of the methods described in various embodiments of this application. The aforementioned storage media include: U disk, mobile hard disk, ROM, RAM, magnetic disk or optical disk and other media that can store program codes.

The above are only specific embodiments of the present application, but the protection scope of the present application is not limited thereto. Any person familiar with the technical field can easily think of changes or substitutions within the technical scope disclosed in the present application. should be covered by the protection scope of this application. Therefore, the protection scope of this application should be subject to the protection scope of the claims.

Claims

A method of assisted driving, characterized by including:

Obtain the real-time driving parameters of the driver when driving the vehicle and the surrounding environment information of the vehicle;

Determine the driver's driving habits based on the real-time driving parameters and the surrounding environment information;

When the driving habit meets the first preset condition, driving reminder information is prompted to the driver.
The method of claim 1, further comprising:

Determine the driver's driving experience based on the real-time driving parameters;

Wherein, when the driving habit satisfies the first preset condition, prompting the driver with driving reminder information includes:

When the driving habit satisfies the first preset condition and the driving experience satisfies the second preset condition, the driving reminder information is prompted to the driver.
The method of claim 1 or 2, wherein prompting the driver with driving reminder information includes:

When it is detected that the vehicle speed exceeds the preset speed, prompt the driver with vehicle speed reminder information, and the vehicle speed reminder information is used to remind to slow down and/or recommend a vehicle speed; and/or

When the other road users are detected, the driver is prompted with yield indication information, and the yield indication information is used to remind to yield to other road users; and/or

When the distance between the vehicle and the vehicle in front is less than or equal to the preset distance, the driver is prompted with vehicle distance reminder information, and the vehicle distance reminder information is used to remind to maintain the vehicle distance and/or the recommended vehicle distance; and / or

When it is detected that the vehicle enters the restricted parking area, temporary parking reminder information is prompted to the driver, and the temporary parking reminder information is used to remind the restricted parking area and/or parking duration; and/or

When at least one of the vehicle lane change, deceleration, other vehicles behind the vehicle, and obstacles on the driving road is detected, driving observation reminder information is prompted to the driver, and the driving observation reminder information is It prompts you to observe the illegal and violation reminder information around the vehicle.
The method according to any one of claims 1 to 3, characterized in that the method further includes:

At the end of the current trip, prompt the data of irregular driving that occurred in the current trip, and/or prompt the comparison results of the data of irregular driving that occurred in the current trip and the data of irregular driving that occurred in the historical trip. .
The method of claim 4, wherein the irregular driving includes the distance between the vehicle and the vehicle in front being less than or equal to a preset distance, failure to give way to other road users, illegal parking, and speeding. , Violate at least one of the traffic rules.
The method according to any one of claims 1 to 5, characterized in that when the vehicle travels to the first road section and the first road section supports intelligent driving, the method further includes:

The driver is prompted to switch the vehicle to intelligent driving mode.
The method according to any one of claims 1 to 6, characterized in that before prompting the driver with driving reminder information, the method further includes:

The driving reminder information is determined based on the surrounding environment information.
The method according to any one of claims 1 to 7, characterized in that the real-time driving parameters include yielding parameters, and the yielding parameters are used to represent that the vehicle gives way to other road users during the current trip. ok behavior.
A device for assisting driving, which is characterized by including:

An acquisition unit, used to acquire the real-time driving parameters when the driver drives the vehicle and the surrounding environment information of the vehicle;

A processing unit configured to determine the driver's driving habits based on the real-time driving parameters and the surrounding environment information;

A prompting unit configured to prompt driving reminder information to the driver when the driving habit satisfies the first preset condition.
A device for assisting driving, which is characterized by including:

Memory, used to store computer programs;

A processor, configured to execute a computer program stored in the memory, so that the device executes the method according to any one of claims 1 to 9.
A driving assistant, characterized in that the driving assistant includes at least one of a virtual image and a physical image, and the driving assistant includes:

A processor, configured to execute a computer program stored in a memory, so that the driving assistant performs the method according to any one of claims 1 to 9; the driving assistant can be carried on a vehicle screen, a head-up display HUD, a vehicle At least one of the voice device and cockpit.
An intelligent vehicle, characterized by comprising the device as claimed in claim 9 or 10, or the driving assistant as claimed in claim 11.
A computer-readable storage medium, characterized in that a computer program is stored thereon, and when the computer program is executed by a computer, the method according to any one of claims 1 to 9 is implemented.
A chip, characterized in that the chip includes a processor and a data interface, and the processor reads instructions stored in the memory through the data interface to execute the instructions as described in any one of claims 1 to 9 method.